on 01/07/2009 02:34 PM PDXRugger wrote:> I realize i am breaking the posting rules by not posting sample code but i
> tried building some sample test code for this problem based on my working
> code and it wasnt producing what i wanted so hopefully a brief explanation
> and my result will allow you guys enough information to offer some advice.
> My result:
>
> allTAZprobs TAZS
> [1,] Numeric,0 640
> [2,] 0.4385542 641
> [3,] 0.2876207 642
> [4,] Numeric,0 643
> [5,] Numeric,0 649
> [6,] Numeric,0 650
> [7,] 0.7543349 652
> [8,] Numeric,0 654
>
> is a dataframe that is built after about 4 iterative processes of looking
up
> some numbers in different tables and plugging them into the next process.
> The "Numeric,0" result is acheived becuase that missing value
didnt get
> through a "greater than" comparison with a random number, that
part is fine.
> What i want the result to be is:
>
> [1,] 0.4385542 641
> [2,] 0.2876207 642
> [3,] 0.7543349 652
>
> throwing out all of the rows with a "Numeric 0" and keeping the
rest. I
> havent been able to find a way to do this while keeping the two colums
> matched. Not sure if i will have to alter things farther up in my code or
> if i can just do some sort of unlist() function to clear out the unwanted
> rows. Again i apoligize for no working code and realize the breach of
> protocol but i hope my question is clear and i hope someone can help,
Cheers
>
> JR
It would be helpful to see the output of:
str(YourResultObject)
as I suspect that it is a matrix (actually perhaps a list with dims) and
not a data frame, given the row indices being output.
If the output of the above looks something like this, with the result
object being called 'MAT':
> str(MAT)
List of 16
$ : num(0)
$ : num 0.439
$ : num 0.288
$ : num(0)
$ : num(0)
$ : num(0)
$ : num 0.754
$ : num(0)
$ : num 640
$ : num 641
$ : num 642
$ : num 643
$ : num 649
$ : num 650
$ : num 652
$ : num 654
- attr(*, "dim")= int [1:2] 8 2
- attr(*, "dimnames")=List of 2
..$ : NULL
..$ : chr [1:2] "allTAZprobs" "TAZS"
Then one approach to subsetting it, would be:
> subset(as.data.frame(MAT), allTAZprobs > 0)
allTAZprobs TAZS
2 0.4385542 641
3 0.2876207 642
7 0.7543349 652
Another possibility would be:
> MAT[sapply(MAT[, 1], length) > 0, ]
allTAZprobs TAZS
[1,] 0.4385542 641
[2,] 0.2876207 642
[3,] 0.7543349 652
But it all depends upon the actual structure of your result object.
A better approach would be to do a check at each step in the simulation
to see if there is a result or not and assign NA if not. Then you can
use something like na.omit() or similar on the final object.
HTH,
Marc Schwartz